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!49575 Fix cordump problem while null input 

Merge pull request !49575 from zhangzhaoju/r1.10
This commit is contained in:
i-robot 2023-03-02 11:19:17 +00:00 committed by Gitee
parent 493275376f b3049a3440
commit ea8aae4ebb
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GPG Key ID: 173E9B9CA92EEF8F
4 changed files with 19 additions and 17 deletions
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8
mindspore/ccsrc/kernel/kernel.h
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@ -412,6 +412,14 @@ inline bool GetDynamicAttrIntValue(const std::vector<KernelTensorPtr> &inputs, c
*attr_value = res.value();
return true;
}
template <typename T>
inline bool CheckNullInput(const std::vector<T> &input_shape) {
// If input_shape.size() == 0, it means a scalar input; If input_shape.size() != 0 and input_shape contains 0,
// it means a null input. Just return a null output.
return input_shape.size() != 0 && std::any_of(input_shape.begin(), input_shape.end(), [](T i) { return i == 0; });
}
#define CHECK_NULL_INPUT(input_shape) mindspore::kernel::CheckNullInput(input_shape)
} // namespace kernel
} // namespace mindspore

14
mindspore/ccsrc/plugin/device/cpu/kernel/xdivy_cpu_kernel.cc
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@ -99,6 +99,9 @@ bool XdivyCpuKernelMod::LaunchKernel(const std::vector<kernel::AddressPtr> &inpu
const std::vector<kernel::AddressPtr> &outputs) {
CHECK_KERNEL_INPUTS_NUM(inputs.size(), INPUT_NUM, kernel_name_);
CHECK_KERNEL_OUTPUTS_NUM(outputs.size(), OUTPUT_NUM, kernel_name_);
if (has_null_input_) {
return true;
}
auto x_addr = static_cast<T *>(inputs[0]->addr);
auto y_addr = static_cast<T *>(inputs[1]->addr);
auto output_addr = static_cast<T *>(outputs[0]->addr);
@ -136,10 +139,6 @@ bool XdivyCpuKernelMod::LaunchKernel(const std::vector<kernel::AddressPtr> &inpu
bool XdivyCpuKernelMod::Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &workspace,
const std::vector<AddressPtr> &outputs) {
const size_t kInputsNum = 2;
const size_t kOutputsNum = 1;
CHECK_KERNEL_INPUTS_NUM(inputs.size(), kInputsNum, kernel_name_);
CHECK_KERNEL_OUTPUTS_NUM(outputs.size(), kOutputsNum, kernel_name_);
return kernel_func_(this, inputs, workspace, outputs);
}
@ -174,6 +173,13 @@ int XdivyCpuKernelMod::Resize(const BaseOperatorPtr &base_operator, const std::v
auto x_shape = LongVecToSizeVec(inputs.at(kIndex0)->GetShapeVector());
auto y_shape = LongVecToSizeVec(inputs.at(kIndex1)->GetShapeVector());
// while has null input, xdivy result is null too
has_null_input_ = CheckNullInput(x_shape) || CheckNullInput(y_shape);
if (has_null_input_) {
return 0;
}
auto out_shape = LongVecToSizeVec(outputs.at(kIndex0)->GetShapeVector());
if (out_shape.size() > MAX_DIMS || out_shape.size() < x_shape.size() || out_shape.size() < y_shape.size()) {
MS_LOG(EXCEPTION) << "For '" << kernel_name_ << "', the dimension of input cannot be greater than " << MAX_DIMS

1
mindspore/ccsrc/plugin/device/cpu/kernel/xdivy_cpu_kernel.h
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@ -58,6 +58,7 @@ class XdivyCpuKernelMod : public NativeCpuKernelMod, public MatchKernelHelper<Xd
std::vector<size_t> index_listx_{};
std::vector<size_t> index_listy_{};
bool is_need_broadcast_{false};
bool has_null_input_{false};
};
} // namespace kernel
} // namespace mindspore

13
mindspore/ccsrc/plugin/device/gpu/hal/device/gpu_common.h
View File

@ -228,19 +228,6 @@ namespace gpu {
#define VARIABLE_NOT_USED(var) \
{ (void)(var); }
template <typename T>
inline bool CheckNullInput(const std::vector<T> &input_shape) {
// If input_shape.size() == 0, it means a scalar input; If input_shape.size() != 0 and input_shape contains 0,
// it means a null input. Just return a null output.
if (input_shape.size() != 0) {
if (std::any_of(input_shape.begin(), input_shape.end(), [](T i) { return i == 0; })) {
return true;
}
}
return false;
}
#define CHECK_NULL_INPUT(input_shape) mindspore::device::gpu::CheckNullInput(input_shape)
inline bool CheckShapePositive(const std::vector<int64_t> &input_shape) {
if (input_shape.size() != 0) {
if (std::all_of(input_shape.begin(), input_shape.end(), [](int64_t i) { return i > 0; })) {